Xincheng Li | Agricultural Engineering | Best Researcher Award

Posted on by sciencefather

Prof Xincheng Li |  Agricultural Engineering |  Best Researcher Award

Associate Professor at  College of Electrical and Mechanical Engineering，Qingdao Agricultural University, China

Xingcheng Li is a Research Assistant at the College of Electrical and Mechanical Engineering, Qingdao Agricultural University. His research focuses on agricultural information technology, sensor development, intelligent agricultural machinery control, and automation technology in livestock and poultry farming. He has published over 10 academic papers, secured 5 national invention patents, and led key research projects at both provincial and national levels. With experience in teaching and developing innovative solutions in agricultural engineering, Li contributes to advancing technological applications in agriculture.

 

Publication Profile

Academic and Professional Background:

Xingcheng Li is a Research Assistant at Qingdao Agricultural University, specializing in agricultural engineering and information technology. He has taught various courses at both undergraduate and graduate levels, including Principles and Applications of Sensors, Agricultural Sensing, and Operations Research. His primary research interests include agricultural information technology, sensor development, intelligent agricultural machinery control, and automation in livestock and poultry farming.

Research and Innovations:

Prof. Li has contributed significantly to the development of agricultural technologies. He has published over 10 research papers and secured 5 national invention patents. His ongoing research includes projects on livestock and poultry disease prevention, as well as participation in key national and provincial R&D programs. Notably, he has led the Shandong Province Agricultural Major Application Technology Innovation Project and the Natural Science Foundation of Shandong Province.

Research Areas:

  • Agricultural Engineering
  • Mechanical Engineering
  • Agricultural Machinery and Equipment Engineering
  • Agricultural Engineering and Information Technology

Publication Top Notes

  1. A seed-epidermis-feature-recognition-based lightweight peanut seed selection method for embedded systems
    Li, D., Huang, J., Li, X., Xu, P., Yun, Y.
    Measurement and Control (United Kingdom), 2024.
    This paper introduces a lightweight peanut seed selection method based on seed-epidermis feature recognition, suitable for embedded systems in agricultural automation.
  2. Optimization Design and Experiment of Automatic Leveling System for Orchard Operating Platform in Hilly and Mountainous Areas
    Shang, H., Li, X., Zhang, C., Hou, Y., Jia, M.
    INMATEH – Agricultural Engineering, 2024, 73(2), pp. 364–374.
    Focuses on optimizing the design and conducting experiments on an automatic leveling system for orchard platforms in challenging terrains.
  3. Domestic Conflicts and Trade Protectionism: Evidence from Tweets
    Kun, L., Xincheng, L., Ming, F.
    China Journal of Economics, 2022, 9(1), pp. 56–84.
    Analyzes the relationship between domestic conflicts and trade protectionism, based on Twitter data analysis.
  4. Grain Yield Data Collection and Service for Heterogeneous Platforms
    Zheng, L., Guo, X., Li, M., Chen, Y., Xiao, C.
    Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering, 2016, 32(9), pp. 142–149.
    This work discusses systems for collecting and providing grain yield data across different agricultural platforms.
  5. Test and Optimization of Sampling Frequency for Yield Monitor System of Grain Combine Harvester
    Li, X., Li, M., Zheng, L., Wang, X., Sun, M.
    Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery, 2015, 46, pp. 74–78.
    Examines the optimization of sampling frequency for a grain yield monitor in combine harvesters.
  6. Modeling Algorithm for Yield Monitor System of Grain Combine Harvester
    Li, X., Sun, M., Li, M., Zhang, M., Wang, X.
    Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery, 2015, 46(7), pp. 91–96.
    Proposes a modeling algorithm for improving the yield monitor system of grain combine harvesters.
  7. Development and Denoising Test of Grain Combine with Remote Yield Monitoring System
    Li, X., Li, M., Wang, X., Sun, M., Sun, H.
    Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering, 2014, 30(2), pp. 1–8.
    This paper focuses on the development and testing of a grain combine equipped with a remote yield monitoring system.
  8. Structure Design and Signal Processing of a New Grain Flow Sensor
    Li, X., Li, M., Zheng, L., Yang, W., Sun, H.
    American Society of Agricultural and Biological Engineers Annual International Meeting, ASABE 2014, pp. 4330–4336.
    Presents the design and signal processing methods for a new grain flow sensor.
  9. A Remote Monitoring System of Automatic Soil Sampler Based on ZigBee WSN
    Yang, W., Li, M., Zheng, L., Li, X., Zhang, M.
    American Society of Agricultural and Biological Engineers Annual International Meeting, ASABE 2013, pp. 4023–4028.
    Describes a remote monitoring system for an automatic soil sampler based on ZigBee wireless sensor networks (WSN).
  10. A Remote Operating System of Grain Yield Monitor
    Li, X., Li, M., Zheng, L., Yang, W., Zhang, M.
    American Society of Agricultural and Biological Engineers Annual International Meeting, ASABE 2013, pp. 4091–4096.
    Introduces a remote operating system for monitoring grain yield during harvesting.

 

Anelia Iantcheva | Agricultural Science | Excellence in Research

Posted on by sciencefather

Prof Anelia  Iantcheva |   Agricultural Science  |  Excellence in Research

Prof. Principal Investigator at  AgroBioInstitute, Agricultural Academy,  Bulgaria

Prof. Anelia Iantcheva is a distinguished researcher in plant genetics and biotechnology, currently serving as a Professor and Principal Investigator at the Agrobioinstitute of the Agricultural Academy in Bulgaria. She obtained her Master’s degree from Sofia University in 1987, followed by a Ph.D. in 1997 and a DSc in 2019 from the Agricultural Academy.

 

Publication Profile

Academic Background:

Prof. Iantcheva earned her Master’s degree from Sofia University in 1987, followed by a Ph.D. from the Agricultural Academy, Bulgaria in 1997, and a DSc degree in 2019. She became a professor and principal investigator at Agrobioinstitute in 2022.

Research Focus:

Her expertise lies in plant genetics, genomics, transcriptomics, molecular biology, and biotechnology of model and grain and forage legumes.

Research Contributions:

Prof. Iantcheva has coordinated several EU-funded projects, including Horizon 2020 “Legumes Translated” and the ongoing Horizon Europe “Legume Generation.” She has published 64 articles in indexed journals and contributed chapters to five books on somatic embryogenesis and genetic transformation.

Innovations:

Her research has led to the development of efficient plant regeneration systems and insertional mutant collections in Medicago truncatula, laying the groundwork for functional genomics in legumes. She has also innovated a low-temperature pre-treatment method for soybean seeds to enhance agricultural practices.

Publication Top Notes

  1. A novel Microbacterium strain SRS2 promotes the growth of Arabidopsis and MicroTom (S. lycopersicum) under normal and salt stress conditions
    • Journal: Planta
    • Publication Date: October 2024
    • DOI: 10.1007/s00425-024-04510-2
    • Contributors: Ho Manh Tuong, Sonia García Méndez, Michiel Vandecasteele, Anne Willems, Anelia Iantcheva, Pham Bich Ngoc, Do Tien Phat, Chu Hoang Ha, Sofie Goormachtig.
  2. Transcriptional and Metabolic Profiling of Arabidopsis thaliana Transgenic Plants Expressing Histone Acetyltransferase HAC1 upon the Application of Abiotic Stress—Salt and Low Temperature
    • Journal: Metabolites
    • Publication Year: 2023
    • DOI: 10.3390/metabo13090994
    • EID: 2-s2.0-85172238091
    • Contributors: T. Ivanova, I. Dincheva, I. Badjakov, A. Iantcheva.
  3. Transition to legume-supported farming in Europe through redesigning cropping systems
    • Journal: Agronomy for Sustainable Development
    • Publication Year: 2023
    • DOI: 10.1007/s13593-022-00861-w
    • EID: 2-s2.0-85146474358
    • Contributors: I. Notz, C.F.E. Topp, J. Schuler, S. Alves, L.A. Gallardo, J. Dauber, T. Haase, P.R. Hargreaves, M. Hennessy, A. Iantcheva, et al.
  4. Auxin and stringolactone interaction in extreme phosphate conditions
    • Book Chapter: In Agricultural Biocatalysis: Biological and Chemical Applications
    • Publication Year: 2022
    • EID: 2-s2.0-85142565230
    • ISBN: 9781000635287, 9781003313144
    • Contributors: M. Revalska, A. Iantcheva.
  5. Functional characterization of Medicago truncatula GRAS7, a member of the GRAS family transcription factors, in response to abiotic stress
    • Journal: Biotechnology and Biotechnological Equipment
    • Publication Year: 2022
    • DOI: 10.1080/13102818.2022.2074893
    • EID: 2-s2.0-85130201236
    • Contributors: M. Revalska, M. Radkova, A. Iantcheva.
  6. Legumes in natural post-fire successions of forest meadows and pastures in Northern Bulgaria
    • Journal: Thaiszia Journal of Botany
    • Publication Year: 2022
    • DOI: 10.33542/TJB2022-1-05
    • EID: 2-s2.0-85133384347
    • Contributors: G. Naydenova, M. Radkova, A. Iantcheva.
  7. Long-lasting low temperature pretreatment of soybean seeds enhances plant field performance and content of free metabolites
    • Journal: Bulgarian Journal of Agricultural Science
    • Publication Year: 2022
    • EID: 2-s2.0-85143811831
    • Contributors: G. Naidenova, I. Dincheva, I. Badjakov, M. Radkova, M. Revalska, A. Iantcheva.
  8. Moldovan soybean varieties testing in the condition of North Bulgaria
    • Journal: Bulgarian Journal of Agricultural Science
    • Publication Year: 2022
    • EID: 2-s2.0-85127731032
    • Contributors: G. Naydenova, M. Radkova, A. Iantcheva.